Electrostatic potential as a reactivity scoring function in computer-assisted enzyme engineering.

Area of Science:

• Biochemistry and Molecular Biology
• Computational Chemistry and Enzyme Engineering

Background:

• Enzyme catalytic efficiency relies on stabilizing reaction transition states, particularly through electrostatic interactions.
• Existing high-throughput methods for assessing electrostatic contributions in enzyme design are scarce.
• Glycoside hydrolases are crucial enzymes for cleaving glycosidic bonds in various carbohydrates.

Purpose of the Study:

• To introduce a computationally accessible metric for evaluating enzyme electrostatic complementarity to transition states.
• To integrate this metric into BindScan, a computational tool for protein engineering.
• To validate the metric's predictive capability in designing glycoside hydrolase variants with enhanced function.

Main Methods:

• Development of an easy-to-compute metric assessing electrostatic complementarity between enzymes and transition states.
• Implementation of the metric within the BindScan computational protocol for mutational analysis.
• Application and validation using datasets of glycoside hydrolases, including Spodoptera frugiperda β-glucosidase (Sfβgly) and Bifidobacterium bifidum lacto-N-biosidase (BbLnbB).

Main Results:

• The metric accurately predicted mutation effects on catalytic efficiency (kcat/KM) for Sfβgly mutants with 77% classification accuracy.
• BindScan identified BbLnbB variants exhibiting significantly improved transglycosylation yields (up to 32%).
• Electrostatic potential and ligand affinity calculations informed a rational design strategy for enhanced glycoside hydrolase variants.

Conclusions:

• The developed electrostatic complementarity metric is a valuable addition to computational enzyme engineering toolkits.
• BindScan, incorporating this metric, effectively aids in predicting and optimizing enzyme performance, particularly for glycoside hydrolases.
• This approach facilitates the rational design of enzymes for synthesizing valuable glycoconjugates and advancing enzyme engineering.